We have all heard about the Nobel Prize. The Nobel Prize is a set of annual international awards bestowed in several categories by Swedish and Norwegian institutions in recognition of academic, cultural, or scientific advances.

The will of the Swedish scientist Alfred Nobel established the five Nobel prizes in 1895. The prizes in Chemistry, Literature, Peace, Physics, and Medicine were first awarded in 1901. The prizes are widely regarded as the most prestigious awards available in the fields of chemistry, literature, peace activism, physics, and medicine.

Between 1901 and 2018, the Nobel Prizes were awarded to 935 people and organizations. With some receiving the Nobel Prize more than once, this makes a total of 27 organizations and 908 individuals.


A bit of history…

Alfred Nobel was born on 21 October 1833 in Stockholm, into a family of engineers. He was a chemist, engineer, and inventor. In 1894, Nobel purchased an iron and steel mill, which he made into a major armaments manufacturer. Nobel amassed a fortune during his lifetime, with most of his wealth coming from his 355 inventions, of which dynamite is the most famous.

In 1888, his brother Ludvig died, but a French newspaper mistakenly ran an obit for Alfred titled, “The merchant of death is dead.” This caused Alfred to suffer such a crisis of conscience, he created a series of awards to honor those who confer the “greatest benefit on mankind” in physics, chemistry, physiology or medicine, literature and peace. The Nobel Memorial Prize in Economic Sciences was added in 1968 in memory of Alfred Nobel.


1901 - 2018

Between 1901 and 2018, the Nobel Prizes and the Prize in Economic Sciences were awarded 590 times to 935 people and organizations. Each Prize consists of a medal, a personal diploma, and a cash award. A lot of Nobel recipients are well known for their accomplishments. Some of the most famous laureates include:

Marie Curie: Chemistry Nobel prize (1911) for the discovery of the elements radium and polonium
Albert Einstein:Physics Nobel prize (1922) for his contribution in theoretical physics
Ernest Hemingway: Literature Nobel prize (1954) for his mastery of the art of narrative
Sir Alexander Fleming: Medicine Nobel prize (1945) for the discovery of penicillin
John Nash: Economics Nobel prize (1994) for his pioneering analysis of equilibria in game theory
Mother Terese: Peace Nobel prize (1979) for founding of the Charity of Missionaries



Let’s begin with some inspirational acceptance speeches for the Nobel Peace Prize.



Load Data

In the datasets tab, you have an option to create the report. But you can’t actually see the data. For our session, I have uploaded the data in Workbooks tab. Let us take a quick look at the data.


For those who don’t have access to the workspace ‘2019 F2F Power BI’, an alternative would be to use Power BI desktop. You can download the data from the link below and use Power BI desktop to load this Excel workbook and create a report. link:https://jamespaultg.github.io/NobelWinnersPowerBIQuerydata.xlsx


Let’s explore the laureates and understand a few more things about the prizes and the people that won them. We have the dataset that includes all the prizes that have been awarded between 1901 and 2018. In order, to explore the data set we first have to see what type of information is in it. We have already uploaded the data set and created a data dictionary that includes all the headings of the dataset.

Data Dictionary

This dataset includes a record for every individual or organization that was awarded the Nobel Prize since 1901. Below we can find the data dictionary, that includes all 12 variables. From now on we will refer to them as features. Let’s spend some time to go though them and understand what kind of information they include.


Feature Definition
ID Unique id assigned to an individual or an organization
agePrizeReceived Age at which the individual received the prize
bornCity City of birth
bornCountry Country of birth
category Physics, Chemistry, Medicine, Peace, Literature, Economics
fullname Name of the individual and organizations that won the prize
gender Male, Female
imageURL URL to the image of the individual or organisation
laureate Type Individual or Organisation
motivation The work for which the prize was awarded
prizeyear The year in which the prize was awarded
prizeyearcategory Combination of the prizeYear and Category


Exploratory Analytics

We have now have read our data set, looked into the data dictionary and know a few more things on the laureates’ features. Let us start analyzing the data with basic questions.

What is the total number of prizes awarded?

We know that a prize for a category could be shared by maximum three individuals. So we can’t just count the total rows in the dataset to get the answer. We are interested in the combination of the prize year and the category, and luckily we have such a field (prizeYearCategory) directly available in the dataset.

As we are going to show only one number, we could use the card visual.


What is the total number of individuals who have won the prize?

Note that there could be individuals and organizations who won the prize more than once. We will find which of them got more than one prize later, but for now remember we are interested in showing the unique number of individuals and organizations. Clue: You need to use count(distinct) and also use Visual level filter. Check out the video!


What is the total number of years the prize was awarded (variable prizeYear)?
What is the total number of (unique) organizations that won the prize?

What is the total number of (unique) organizations that won the prize?

You could also change a visual. Let us say, instead of the card visual we want to see in a bar graph the count of both the individuals and the organizations.




What is the total number of prizes awarded per category?

Let us look at the prizes awarded per category. We want to visualize the number of prizes per category, a bar chart would be ideal for this. Try to create the bar chart yourself and see if your visual matches the one shown here.



What is the prize distribution over the years?

We would like to see the number of prizes over the years. A column chart would be suited for this.

We see some years(1940, 1941 and 1942) during the second world war, that there were no prizes awarded. We also see an increasingly that the prizes are being shared(awarded per category to more individuals).

And if we look at the bar chart for prizes per category, we see that economics has the lowest number. Let us see if we can find an explanation for it. Click on the bar for economics in the bar graph, we notice that it highlights prizes related to economics in the column chart. This shows the nice visual interaction that is possible in Power BI. From this we see clearly that the prize for economics started only from 1969 onwards, which explains why we have such a low number.




Add a new page in the report and give it the name ‘WHO’. Try if you can answer the below questions by creating bar chart yourself and see if your visual matches the one shown here.

What is the number of prizes won by males and females?

We could answer this by creating a bar chart (refer to the video-4 for example), with gender as axis and the ‘count of id’ as value. Please remember to include filter to select only individuals.

Does the gender distribution vary over the various prize categories?

Let us create a bar chart with category(exactly same as in video-4) and then have the field gender in the legend. We see that the distribution of women is quite low in Economics, followed by Physics.

Would be interesting to see the percentage, for which we could use the 100% stacked bar chart visual. Try changing the bar chart you created to a ‘100% stacked bar chart visual’ to get the below visual.


Now let us see how to represent a list or table.

What is the minimum and the maximum age of the recipients per category?

We want to have a table with the minimum and maximum age listed per category. We have a visual called ‘Table’, that could be used for this.



Now try to answer the below question with a table visual

Who got more than one prize? Give a list with the fullname, number of prizes won, laureate type.

We noticed earlier from the distinct count of individuals and organizations that there are some who got more than one prize. Let us have a look to see who they are. Again a table visual would be best fit for this. We are interested in the names of the individual / organization, along with the total number of prizes they won. We filter the visual where the count of prize year is more than one.






Add a page in the report and give it a name ‘WHERE’. And try answering the following questions.

  1. Visualize in a bar chart the number of laureates per country
  2. Visualize in a world map the number of laureates per country
  3. A table with the name of the recipients, photo, city of birth, prize category, year and motivation

Does your visualization match the ones shown below?



Don’t worry if you didn’t get it right. Just follow the notes below for help.

Visualize in a bar chart the number of laureates per country
This is similar to the bar chart created for visualizing the number of prizes won by individuals and organizations. If you are struck follow video-4.



Visualize in a world map the number of laureates per country

We could use a ‘map’ visual. The size of the bubble could be varied based on the number of laureates per country. If we hover our mouse over a particular bubble, it would be nice to see some information on the recipients. We can use the ‘tool tip’ for this and information such as name, prize category, prize year.



Show the list of recipients
Try the ‘table’ visual with the name of the recipients, photo, city of birth, prize category, year and motivation. If you are struck follow video-7.

You can refer the video if you have trouble creating the visuals yourself.



Visual interaction

Now when we select a country from the bar chart, we see the table contents automatically filtered and shows the list of recipients from that country. Same way, we can also select a point in the map to see only the persons from that particular country listed in the table.


Finally let’s spend some time inseeing how we can create a dashboard.





This is the end of the hands-on exercise.
We hope you enjoyed it and learned some useful skills!